Obesity is a complex disease in which people with the same body mass index can have very different metabolic profiles. This variability makes it difficult to apply universal prevention and treatment strategies and highlights the need to move towards more personalised nutrition approaches.
In addition, maintaining adherence to nutritional recommendations and ensuring continuous follow-up outside clinical settings remain major challenges for both healthcare professionals and patients.
The OBINTER project integrated omics technologies, digital tools and personalised follow-up to help people with obesity improve their health in a sustainable way.
The platform combined information from:
AZTI contributed its expertise in personalised nutrition, omics analysis and biomarker development to characterise the metabolic status of participants and develop models capable of identifying risk profiles beyond traditional indicators.
All this information was integrated to generate personalised nutritional recommendations tailored to the specific needs of each individual.
The studies carried out have shown that the lipid composition of cell membranes can distinguish between different metabolic profiles even in people with similar anthropometric characteristics, opening up new opportunities for more precise nutritional intervention.
OBINTER has also helped advance towards a more personalised, data-driven model of care by enabling:
Sectors: Food and Health
Research lines: Personalised nutrition and health
Research sublines: Precision nutrition technologies, The impact of food on human health